Ministry of Defence

Government Agency (Other)

1119

In support of this national response, this project is undertaking the following areas of work. As COVID-19 caseloads in England appear to have reached the first peak, to ensure continued response to the epidemic is most effective, it is imperative that we better understand (retrospectively and prospectively) the geographical evolution of COVID-19 and localised areas in space-time at higher risk of severe disease burden and mortality. Integrated daily small-area spatial analysis of COVID-19 syndromic profiling and duration of symptoms (using self-reported data from >2million users of the COVID Symptom Tracker) versus Independent Peer Review Not required IF YOU HAVE TICKED 'NOT REQUIRED' PLEASE SPECIFY THE REASONS: This project is being undertaken in the national interest during a national emergency, with information being provided across governments and health authorities. Research Ethics Not required THE PROJECT USES WILL USE ONLY ANONYMISED DATA, AND THEREFORE RESEARCH ETHICS REVIEW IS NOT REQUIRED Yes 2 of 7 confirmed cases and deaths within a stochastic space–time susceptible-infected-died/recovered model framework will aid in early identification of local authorities/trusts at higher risk for increased caseloads and/or higher mortality. Assessing the impact of mobility, population- and commuter-density on differences in caseloads at local authority scale will not only allow assessment of the impact that social distance measures have had on the magnitude and timing of the first peak, but also allow counterfactual assessment of what this magnitude may have been in the absence of these non-pharmaceutical interventions (NPIs). More importantly as we enter the first downward phase of local outbreaks, this work will help inform when it might be safe to start lifting social distancing measures at small-area scale and whether this strategy needs to be regionally staggered. Lastly inclusion of important predictors in the infection and death compartments of the model, such as underlying chronic disease prevalence, age-structure, social deprivation and ethnicity, will also be key to explain potential differences in COVID-19 mortality rates across local authorities and between key socio-demographic groups.

Specifically this project aims to: 1. Accurate characterisation of the space-time evolution of the COVID-19 outbreak in England and quantification of the impact of important contextual risk factors and NPI’s at small-area scale. 1. Accurate characterisation of the space-time evolution of the COVID-19 outbreak in England and quantification of the impact of important contextual risk factors and NPI’s at small-area scale providing improved understanding of: a) how the outbreak has/is evolving in space-time and quantification of the likely impact of NPIs on further reduced the rate of spread; b) the impacts local mobility, deprivation, age-structure and underlying chronic disease burden on caseloads and deaths at small-area scale, to inform measures addressing inequities in disease burden; c) how local hospital capacity indicators compare against projected severe caseloads, as an ongoing pre-emptive planning/case management optimisation tool. 2. Determine the utility of self-reported C-19 COVID Symptom Tracker data as an early warning system at small-area scale 3. Assess the impact of easing of social distancing (NPI’s) to help inform contingency planning/strategies for subsequent waves and/or future epidemics 4. Support optimal design of ‘test track and isolate’ strategies needed to maintain control of COVID-19 Anticipated outcomes of the project are: 1. Accurate characterisation of the space-time evolution of the COVID-19 outbreak in England and quantification of the impact of important contextual risk factors and NPI’s at small-area scale providing improved understanding of: a) how the outbreak has/is evolving in space-time and quantification of the likely impact of NPIs on further reduced the rate of spread; b) the impacts local mobility, deprivation, age-structure and underlying chronic disease burden on caseloads and deaths at small-area scale, to inform measures addressing inequities in disease burden; c) how local hospital capacity indicators compare against projected severe caseloads, as an ongoing pre-emptive planning/case management optimisation tool. 2. Determine the utility of selfreported C-19 COVID Symptom Tracker data as an early warning system at small-area scale: in a joint space-time framework with lagged confirmed hospital case/death data, we will validate the predictive performance of this tracking tool as a pre-emptive community signal prior to localised increases and patient demand for case management and support. 3. Confirm if staggered removal of NPI’s presents a viable strategy, to help inform contingency planning/strategies for subsequent waves and/or future epidemics: accurately charting/modelling COVID-19 outbreak dynamics at small-area scale and by day from outbreak inception against mobility patterns will allow quantification of the effect at small area scale and identify potential key windows in space-time for more aggressive/active containment and mitigation activities at localised scale rather than through adoption of more generalised interventions/recommendations. 4. Support optimal design of ‘test track and isolate’ strategies needed to maintain control of COVID-19 by enabling more flexible thinking around the kind of contacts which are important.

07/05/2020

Anonymous

(e) processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

(j) processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Not applicable

Not applicable

TRE